The present invention relates to speech detection. More specifically, the present invention relates to detecting the presence of speech of a desired speaker based on a multi-sensory transducer input system.
In many different speech recognition applications, it is very important, and can be critical, to have a clear and consistent audio input representing the speech to be recognized provided to the automatic speech recognition system. Two categories of noise which tend to corrupt the audio input to the speech recognition system are ambient noise and noise generated from background speech. There has been extensive work done in developing noise cancellation techniques in order to cancel ambient noise from the audio input. Some techniques are already commercially available in audio processing software, or integrated in digital microphones, such as universal serial bus (USB) microphones.
Dealing with noise related to background speech has been more problematic. This can arise in a variety of different, noisy environments. For example, where the speaker of interest in talking in a crowd, or among other people, a conventional microphone often picks up the speech of speakers other than the speaker of interest. Basically, in any environment in which other persons are talking, the audio signal generated from the speaker of interest can be compromised.
One prior solution for dealing with background speech is to provide an on/off switch on the cord of a headset or on a handset. The on/off switch has been referred to as a “push-to-talk” button and the user is required to push the button prior to speaking. When the user pushes the button, it generates a button signal. The button signal indicates to the speech recognition system that the speaker of interest is speaking, or is about to speak. However, some usability studies have shown that this type of system is not satisfactory or desired by users.
In addition, there has been work done in attempting to separate background speakers picked up by microphones from the speaker of interest (or foreground speaker). This has worked reasonably well in clean office environments, but has proven insufficient in highly noisy environments.
In yet another prior technique, a signal from a standard microphone has been combined with a signal from a throat microphone. The throat microphone registers laryngeal behavior indirectly by measuring the change in electrical impedance across the throat during speaking. The signal generated by the throat microphone was combined with the conventional microphone and models were generated that modeled the spectral content of the combined signals.
An algorithm was used to map the noisy, combined standard and throat microphone signal features to a clean standard microphone feature. This was estimated using probabilistic optimum filtering. However, while the throat microphone is quite immune to background noise, the spectral content of the throat microphone signal is quite limited. Therefore, using it to map to a clean estimated feature vector was not highly accurate. This technique is described in greater detail in Frankco et al., COMBINING HETEROGENEOUS SENSORS WITH STANDARD MICROPHONES FOR NOISY ROBUST RECOGNITION, Presentation at the DARPA ROAR Workshop, Orlando, Fl. (2001). In addition, wearing a throat microphone is an added inconvenience to the user.